Puritan's founder, Abraham Penn, taught a valuable lesson that has been a part of the Puritan Tradition since 1919 when he said: "I'd rather make a friend than make a sale." Since that time, Puritan has made many, many friends and continues to do so to this day.
He began in a modest Plymouth, MA store he and his partner purchased for $4,000. They believed they had to provide classic, impeccably tailored clothing and personalized service in order to succeed, and each had to be of the highest quality possible. In 1925, after expanding the business to include uniform sales, they expanded geographically with the first of the on-Cape stores. It was located in Chatham, MA, and they chose that location in order to service the nearby Coast Guard Station, as well as Chatham residents. It was the uniform sales that proved critical in helping the still young company survive the Depression years.
Abe's sons, Milton and Howard, both joined their father's business at early ages, working in the Plymouth store filling orders and wrapping packages. When the Hyannis store was opened, they could be seen sweeping sidewalks and washing the storefront windows. These experiences taught them the value of hard work and attention to detail, traits that would serve them well when they assumed responsibility for the stores later in life. In turn, they passed these values on to their own children, so that Puritan today is in the hands of third generation Penns.
Today, Rick and Jim Penn, the 3rd generation of the Penn Family bring to the office every day the lessons they learned from their grandfather and fathers. They manage the operation of a 50+ person sales force and support staff for the five locations, which includes four Puritan Cape Cod stores and a company owned Vineyard Vines concept store.
The philosophy instilled in them by Abraham, Milton, & Howard, still forms the foundation of their business. The core value of building relationships established by their grandfather, Abraham Penn over 90 years ago, is still relevant today. It is a testament to the Penn family that they also practice what they preach when it comes to relationships with more than half of their associates achieving more than 10 years of service, and some for more than a quarter century!


We got mices!
- benchmark ubiquitous solutions
- brand 24/7 experiences
- evolve bricks-and-clicks interfaces
- embrace collaborative partnerships
- orchestrate enterprise users
- extend bricks-and-clicks channels
- enable frictionless partnerships
- facilitate magnetic initiatives


Save Kerala
Name
Number of People to save
{% for row in rows %}
{{row[0]}}
{{row[1]}}
{% endfor %}
Home


Where possible, links have been added from the programme below to the corresponding tutorials and lecture slides. Additional links will be added as they become available.
| Sunday 2019/02/17 |
Monday 2019/02/18 |
Tuesday 2019/02/19 |
Wednesday 2019/02/20 |
Thursday 2019/02/21 |
Friday 2019/02/22 |
|
|---|---|---|---|---|---|---|
| 09:00 | Alexei Drummond Bayesian Phylogenetics and BEAST |
Remco Bouckaert Phylogenetic model selection and averaging |
Tim Vaughan, Jana Huisman, Nicola Müller Bayesian Phylodynamics: Skylines, Fossilization and Structure |
Mike Lee Bayesian phylogenetics for phenotypic and palaeontological datasets (part 1, part 2) |
Sebastián Duchêne Tip-dating and phylodynamics |
|
| 11:00 | Morning Tea | Morning Tea | Morning Tea | Morning Tea | Morning Tea | |
| 11:30 | Tim Vaughan
First Steps in BEAST 2 (lecture, tutorial) |
Remco Bouckaert Substitution model averaging (tutorial) |
Mike Lee Arid biomes as a source, not sink, for Australian lizard biodiversity (public lecture) |
Jana Huisman Fossilized birth-death model analyses (tutorial) |
Nicola Müller Isolation with Migration using Coupled MCMC (tutorial) |
|
| 12:30 | Free afternoon (packed lunch provided) |
|||||
| 13:00 | Lunch | Lunch | Lunch | Lunch | ||
| 14:00 | Jana Huisman Prior Selection & Troubleshooting (lecture, tutorial) |
Simon Ho Molecular Dating (lecture) |
David Duchêne Species trees and gene trees (lecture) |
Tim Vaughan Bacterial genomics (lecture, tutorial) |
||
| 15:00 | Jérémie Sciré, Nicola Müller Analyzing structured populations under birth-death and coalescent models (tutorial 1, tutorial 2) |
|||||
| 15:30 | Afternoon Tea | Afternoon Tea | Afternoon Tea | |||
| 16:00 |
Welcome and registration (Courtyard Cafe, University of Sydney) |
Nicola Müller Skyline Plot Tutorial (lecture, tutorial) |
Cara Van Der Wal, Daej Arab, Yi-Kai Tea Divergence time estimation (tutorial) |
Departure | ||
| 16:30 | ||||||
| 17:00 | ||||||
| 18:00 |
Buffet dinner cruise (Sydney Harbour, Depart from King St Wharf) |
|||||
| 18:30 | Dinner (Thai Pothong, Newtown) |
You are required to bring your own laptop to the workshop. Power strips are available for each participant to keep their devices charged during the workshop. The software below must be installed prior to arrival.
We are aware that some of the workshop participants do not have a mathematical background and may have difficulty understanding some of the theory. The two links below can help to refresh the basic concepts, but are by no means meant to be comprehensive resources.
The books below are not all focused on BEAST or even Bayesian phylogenetics. However, each of the books contains at least one background chapter on the theory of molecular evolution, as well as more in-depth chapters on the models implemented in BEAST and BEAST 2. Most of the books also contain at least some discussion of Bayesian inference.
In addition, the following review papers might be useful:


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Get the latest release stats!
...and get the latest release stats like download counts, release dates, authors for any Github project.


The Commandline and Git toolkit -List.
Simple, clean, $ Commandlines List for Mac Os X/ Unix & Linux!
© Developed & Maintenance by Lucas Gatsas. Site Developed with Bootstrap V.3.3.4 and Jekyll. V.2.5.3 - BlogWare hosted by Github.
April 1st, 2015


This page was built to show some of the projects of the course. It was used as a practice page for the projects.
You can check the projects below.
Front-End Projects
Back-End Projects
Some Project
This page was built to show some of the projects of the course. It was used as a practice page for the projects.
You can check the projects below.
Some Project


{{raw.enabled | checkmark}}Set to automatically re-enable at {{raw.disableExpiration | dateFormat}}
{{store.prepend_constituent | checkmark}}If enabled, all new constituents which are added not manually(like promotion) will be at the top of constituents list


Important Concepts of the Web
The basics of the web
The web
HTML
URLs
HTTP
Web Applications
World wide web
Collection of HTML doc's
hyper text markup language = HTML
hyper links (links)
Invented 1990's over 30billion pages
Major Pieces
YOU -> Your computer+browser -> the internet-> Servers
HTTP: The main protocol of the web
Servers: Computers that host the files that make up the web
Internet: The worlds largest computer network.
Browser: A program that runs on your computer to display files found on the web.
HTML:
HTML Stands for Hypertext markup language. HTML documents from the majority of the content on the web. HTML Documents contains different types of markups.
HTML Markups:
B Tag:
context
B = Bold
EM Tag
Italics
HTML Attributes
contents
anchor = a tag
reddit.com
Image tag:
IMG
^ img src is required; broken requests
src = source
example:
Whitespace:
text on multiple lines -> Text on multiple lines.
BR tag =break
P tag = paragraph
inline/block:
HTML elements are either inline or block. Block elements form an "invisible box" around the content inside of them.
br tag - inline
p tag - block
text = line ends here and makes a new line
text
text = a invisible box
span/div:
text text
inline block
Elements that are inline:
a = anchor tag
span tag
img tag
strong tag
br tag


Adding Notes data to Websphere content manager via RSS
Websphere Content Manager (WCM) can aggregate information from various sources in many formats. A quick and dirty way to add Domino data is to use RSS. The simplest way is to add a page (not an XPage, a Page), define its content type as
Thereafter create a view with passthrou HTML with all the values for an
application/rss+xml
and add a few lines to it:
<rss version="2.0">
<channel>
<title><Computed Value></title>
<link><Computed Value>feed.xml</link>
<description>Extraction of data from the Audience Governance database</description>
<lastBuildDate><Computed Value></lastBuildDate>
[Embedded view here]
</channel>
</rss>
Thereafter create a view with passthrou HTML with all the values for an
item
element. Of course that is super boring, therefore you can use the following code to speed this up.Read more
Posted by Stephan H Wissel on 27 July 2015 | Comments (0) | categories: IBM Notes Java


Tests that evaluating 'console.log()' in the console will have access to its outer scope variables. Bug 60547.


Information systems are applications incorporating a database for storing and processing data. Upgrading information systems requires updating the application logic, modifying the database schema, and adopting the data accordingly. Previous research focuses either on schema evolution or on application logic updates. In this paper, we take a holistic approach by addressing the combination. First, we elaborate the three main upgrade patterns: install & copy, rejuvenation/delta only, and rejuvenation/verified. Second, we introduce our upgrade correctness concept. It is a formal correctness criterion for deciding whether an upgrade succeeded. Third, we discuss implementation patterns. Our insights base on various upgrade projects from stand-alone applications to multi-tenant systems having affected more than one hundred banks.


Attn: Sir/Madam, {HIGHLY CONFIDENTIAL} (RE: TRANSFER OF (THIRTY SIX MILLION SEVEN HUNDRED AND FIFTY NINE THOUSAND POUNDS STERLINGS) RE: TRANSFER OF 36,759,000.00 MILLION POUNDS TO YOUR ACCOUNT. My name is Mr.Bernard Martin and I work in the International Operation Department in a Bank here in London. I feel quite safe dealing with you in this important business.Though, this medium (Internet) has been greatly abused, I choose to reach you through it because it still remains the fastest medium of communication. However, this correspondence is unofficial and private, and it should be treated as such. At first I will like to assure you that this transaction is 100% risk and trouble free to both parties. WE WANT TO TRANSFER OUT MONEY FROM OUR BANK HERE IN LONDON. THE FUND FOR TRANSFER IS OF CLEAN ORIGIN. THE OWNER OF THIS ACCOUNT IS A FOREIGNER, a program leader. Until his death,The Late Prime Minister, Mr. Rafik Hariri, has a huge investment here in the United Kingdom and all over the world, as a matter of fact he has the sum of(THIRTY SIX MILLION SEVEN HUNDRED AND FIFTY NINE THOUSAND POUNDS STERLINGS) in his account here in London which he deposited as a family valuables.The family do not know about this deposit.I was on a routine inspection that I discovered a dormant domiciliary account with a BAL. Of (THIRTY SIX MILLION SEVEN HUNDRED AND FIFTY NINE THOUSAND POUNDS STERLINGS) on further discreet investigation, I also discovered that the account holder has passed away (dead) leaving no beneficiary to the account. The bank will approve this money to any foreigne r because the former operator of the a/c is a foreigner. I am certainly sure that nobody will come again for the claim of this money. A foreigner can only claim this money with legal claims to the account Holder, Therefore I need your cooperation in this transaction. I will provide all necessary information needed in order to claim this money.Hoping in God that you will never let me down now and in future.o.k! Rafik Bahaa Edine Hariri (November 1, 1944 - February 14, 2005), married to Nazek Audi Hariri, was a Lebanese self- made billionaire and business tycoon, and was five times Prime Minister of Lebanon (1992-1998 and 2000-2004) before his last resignation from office on October 20, 2004. The late Rafik Hariri died on February 14, 2005 when explosives equivalent to around 300 kg of C4 were detonated as his motorcade drove past the Saint George Hotel i n the Lebanese capital, for more information please log on to(http://www.hariri.info/) I WANT TO TRANSFER THIS MONEY INTO A SAFE FOREIGN ACCOUNT ABROAD BUT I DON'T KNOW ANY FOREIGNER WHOM I CAN TRUST, I KNOW THAT THIS MESSAGE WILL COME TO YOU AS A SURPRISE AS WE DON'T KNOW OURSELVES BEFORE, BUT BE SURE THAT IT IS REAL AND A GENUINE BUSINESS.  Let me hear from you urgently through this Email<bernardmartin01@rediffmail. com> Best Regards Mr.Bernard Martin.


Section 7.6 Bayes' Theorem
Let's begin with some probability. One way to represent probability is with a number between 1 and 0. A quick way to remember how to calculate some probabilities is
Consider the probability of rolling a number greater than 4 on a six sided die. There are 2 numbers greater than 4 (specifically, 5 and 6), and 6 total possibilities, so the probability of rolling greater than 4 is \(\frac{2}{6}\) or approximately 0.33333.
If events \(A\) and \(B\) do not influence the probability of each other happening (they are independent events), you can calculate their joint probability by just multiplying their probabilities together. Consider the act of rolling two dice. An example of two independent events are \(A\text{:}\) rolling a 6, and then \(B\text{:}\) rolling an odd number. These events are independent because rolling a 6 with die 1 does not change the probability of rolling an odd number with die 2. Observe that \(P(A)=\frac{1}{6}\) and that \(P(B)=\frac{3}{6}\) since there are three odd numbers on a die. We can then use the formula
and plug in the values we just determined to get
Consider the space of all possible outcomes of rolling two dice, all 36 outcomes. These individual outcome probabilities are recorded in the following table:
| \(A \backslash B\) | 1 | 2 | 3 | 4 | 5 | 6 |
| 1 | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) |
| 2 | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) |
| 3 | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) |
| 4 | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) |
| 5 | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) |
| 6 | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) | \(1 / 36\) |
The probability of rolling a six for one of the rolls is represented in the bottom row. The probability of rolling a six and rolling either a 1,3, or 5 are represented by the corresponding columns in the last row, If you add them up, you get a 3/36 probability.
Now consider the game of craps. One desirable outcome of the game is to roll two dice that sum to 7 or 11. An example of two events are \(A\text{:}\) rolling a number less than 4, and \(B\text{:}\) rolling two dice that sum to 7. Let's say we wanted to know the probability of rolling two dice that sum to 7, given that the first roll is less than 4. In math notation, we write this probability as \(P(B \vert A)\text{.}\)
You may remember from a high school algebra course that
and then you can use this formula to determine the probability that the two dice sum to 7 given that the first roll is less than 4.
If we take this formula and multiply both sides by \(P(A)\text{,}\) we see that
But suppose we swap events \(A\) and \(B\text{.}\) Then notice that
If we solve this for \(P(A,B)\) we get
You can also calculate this probability in terms of the probability of event \(B\text{.}\)
But notice that the probability of \(A\) and \(B\) is the same as the probability of \(B\) and \(A\text{,}\) so we know \(P(A,B)=P(B,A)\text{.}\) Plugging in the formulas we just determined for each of these, we see that
Solving for \(P(A \vert B)\text{,}\) we obtain Bayes' Theorem:
You might ask, why would you do all of this manipulation? This theorem is now ubiquitous in science, machine learning, and artificial intelligence. As we will see in later sections, Bayes' theorem allows you to make predictions and inferences with what seems like incomplete data.
Subsection 7.6.1 Using Bayes' Theorem to calculate false positives
One consideration that policy makers and public health experts have to take into account when selecting tests for a disease is the false positive and false negative rate. These can be thought of as the probability of testing positive when a person does not have the disease (false positive) and the probability of testing negative when a person actually has the disease.
Let's say we are trying to find the probability of a false negative. This is arguably the scarier scenario from a public health scenario, as we saw with asymptomatic carriers of the COVID-19 virus. If someone thinks they are negative but are actually positive, they might spread the disease to many others!
Let's say the Umbrella corporation is attempting to test a new rapid COVID test. They start by randomly selecting 100,000 people and administering two tests: their new rapid test and a 100 percent reliable (but slow) Super PCR test. (In reality PCR tests are not 100% effective.)
Note: "negative" means tested negative, not actually negative, "positive" means tested positive, not actually positive.
In the broader population, the prior belief of the Centers for Disease Control and Prevention is that the positive rate for the disease is 1 percent. Therefore, \(P(infected) = 0.001\text{.}\) The manufacturers of the test have taken a random sampling of people and administered the test. Of the 100,000 people, 98,500 people tested negative. Therefore \(P(negative) = 98,500 / 100,000 = 0.985\text{.}\)
Because there are many more non-infected people, and a low negativity rate for the test, the company decides to take the 1,500 people who tested negative using the Super PCR test. All of these people are actually infected, because the other test is 100 pct. accurate. Of these 1,500 people who are actually infected, 1,000 tested positive and 500 tested negative using the rapid test. Therefore, \(P(negative \vert infected) = 500/1,500 = 1/3\text{.}\)
We now have everything we need to make the false negative calculation.
This might not seem like a high probability, but consider the implications for a city of 1,000,000 people; that's \(0.00032833 \times 1,000,000 = 328\) people walking around the city, spreading disease!


Nodemailer is able to sign all messages with DKIM keys. This means calculating a signature for the message and adding it as an additional header (or headers, if you use multiple keys) to the message.
The drawback on DKIM signing is that Nodemailer needs to cache the entire message before it can be sent, unlike normal sending where message output is streamed to SMTP as it is created and nothing needs to be cached. For small messages it does not matter, for larger messages Nodemailer offers an option to cache messages not in memory but on disk. In this case Nodemailer starts buffering the message in memory and if the message size reaches a certain treshold, it gets directed to a file on disk. Once signature is calculated and sent to SMTP, Nodemailer streams the cached message from disk to SMTP.
In general DKIM signing should be fast and effective.
DKIM signing can be set on the transport level (all messages get signed with the same keys) and also on the message level (provide different keys for every message). If both are set, then message level DKIM configuration is preferred.
In both cases you need to provide a dkim
object with the following structure
message-id:date:from:to...'
)'message-id:date'
to prevent signing these values.Assumes that there is a public key available for 2017._domainkey.example.com. You can test if the key exists or not with the dig tool like this
dig TXT 2017._domainkey.example.com
let transporter = nodemailer.createTransport({
service: 'Gmail',
dkim: {
domainName: 'example.com',
keySelector: '2017',
privateKey: '-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBg...'
}
});
Assumes that there is a public keys available for 2017._domainkey.example.com and 2016._domainkey.example.com
let transporter = nodemailer.createTransport({
service: 'Gmail',
dkim: {
keys: [
{
domainName: 'example.com',
keySelector: '2017',
privateKey: '-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBg...'
},
{
domainName: 'example.com',
keySelector: '2016',
privateKey: '-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBg...'
}
]
cacheDir: false
}
});
Do not sign by default. Provide DKIM key values separately for every message.
let transporter = nodemailer.createTransport({
service: 'Gmail'
});
let message = {
from<EMAIL_ADDRESS>to<EMAIL_ADDRESS>subject: 'Message',
text: 'I hope this message gets read!',
dkim: {
domainName: 'example.com',
keySelector: '2017',
privateKey: '-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBg...'
}
};
Messages larger than 100kB are cached to disk
let transporter = nodemailer.createTransport({
service: 'Gmail',
dkim: {
domainName: 'example.com',
keySelector: '2017',
privateKey: '-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBg...',
cacheDir: '/tmp',
cacheTreshold: 100 * 1024
}
});
This is needed when sending mail through SES that has its own Message-ID and Date system.
let transporter = nodemailer.createTransport({
service: 'Gmail',
dkim: {
domainName: 'example.com',
keySelector: '2017',
privateKey: '-----BEGIN PRIVATE KEY-----\nMIIEvgIBADANBg...',
skipFields: 'message-id:date'
}
});


Fabric is an engaging, lightweight, and secure classroom whiteboard for teachers and students alike. It uses Python Socket technology to enable communication between users, and is convenient for those who enjoy a streamlined collaborative experience.


Press the right arrow to continue >
End-users requirements have evolved. People are tired of slow, unreactive Web sites. They want:
Those websites should be delivered fast.
Waiting 1 minute for your application to "deploy" is not acceptable anymore
Modern websites should be able to handle huge numbers of concurrent users
All using massive RESTful applications, which will hit your back-end servers hard
npm install -g generator-jhipster
jhipster
npm start
npm test
Hello, world!
./mvnw spring-boot:run
./gradlew bootRun
@Service
@Transactional
public class UserService {
@Autowired
private UserRepository userRepository;
}
@Entity
public class User implements Serializable {
@Id
private String login;
}
public interface PersistenceAuditEventRepository extends JpaRepository<PersistentAuditEvent, String> {
List<PersistentAuditEvent>
findByPrincipalAndAuditEventDateGreaterThan(String principal, LocalDateTime after);
}
@Entity
@Cache(usage = CacheConcurrencyStrategy.NONSTRICT_READ_WRITE)
public class User implements Serializable {
}
@RestController
public class AccountResource {
@PostMapping("/account")
public void saveAccount(@RequestBody UserDTO userDTO) {
userService.updateUserInformation(userDTO);
}
}
Hello, world
@Timed
public void saveAccount(@RequestBody UserDTO userDTO) {
userService.updateUserInformation(userDTO);
}
At the time of this writing (March, 2018), JHipster has:
npm install -g yo
npm install -g generator-jhipster
And use the embedded Maven wrapper to run it
(hot reload of your application will work automatically)
jhipster
./mvnw
Live reload of your client-side code (HTML, CSS, TypeScript) works thanks to Webpack and Browsersync. Edit any file and your browser will refresh automatically:
npm start
jhipster entity Foo
(Using Docker to run the database)
./mvnw -Pprod package
docker-compose -f src/main/docker/mysql.yml up -d
java -jar target/*.war


-
Stage 1
- $IMSL Token Minting .
- Initial Liquidity Offer (ILO).
- Team Emblems Airdrop (NFTs Airdrop #1).
- CoinMarketCap, Coingeko, and PancakeSwap Listing .
- $IMSL Contract Audit.
-
Stage 2
- The Rules (
DAO #1)
- Teams BEP20 Tokens Minting.
- Teams Tokens Liquidity Pools vs $IMSL.
-
Stage 3
- User Profiles.
- Guest Teams Draft Beta Season (DAO #2).
- Pre-Beta Season Collectibles (NFT Airdrop #2).
-
Stage 4
- Mobile App. (Beta Release)
- Season Beta Draw.
-
Stage 5
- Season Beta Launching (Oracles/Binary Pools).
- Teams Tokens Liquidity Farms on PancakeSwap.
- Official Store ($IMSL and Teams Tokens Payment Platform).
-
Stage 6
- Off-Season Lottery (NFTs Airdrop #3).
- Off-Season Challenges.
Go back to the top


Take a tour of TheRemoteLab to know more on how we can assist you get the best of DevOps practices implemented in your business
Get Started!Ready to start your next project with us? That's great! Give us a call or send us an email and we will get back to you as soon as possible!


Click the dots to make them explode.
Don't need to rush things, though: the closer you get to the explosion, the more points you earn!
Pay attention to the wandering dots and don't let them go away: if you click them the background turns red and the madness begins!
Swipe as much as you can and make plenty of points destroying multiple dots with a single gesture.
Arcade Mode
A race against time: unlock levels by collecting points before the countdown reaches zero
Survivar Mode
Don't make them explode! Three lives at your disposal to earn as much points as you can
Level 1
▶
:
Timer:
Points:
Level:


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| I l@ve RuBoard |
Pragmatic Programmers manipulate text the same way woodworkers shape wood. In previous sections we discussed some specific tools—shells, editors, debuggers—that we use. These are similar to a wood-worker's chisels, saws, and planes—tools specialized to do one or two jobs well. However, every now and then we need to perform some transformation not readily handled by the basic tool set. We need a general-purpose text manipulation tool.
Text manipulation languages are to programming what routers[8] are to woodworking. They are noisy, messy, and somewhat brute force. Make mistakes with them, and entire pieces can be ruined. Some people swear they have no place in the toolbox. But in the right hands, both routers and text manipulation languages can be incredibly powerful and versatile. You can quickly trim something into shape, make joints, and carve. Used properly, these tools have surprising finesse and subtlety. But they take time to master.
[8] Here router means the tool that spins cutting blades very, very fast, not a device for interconnecting networks.
There is a growing number of good text manipulation languages. Unix developers often like to use the power of their command shells, augmented with tools such as awk and sed. People who prefer a more structured tool like the object-oriented nature of Python [URL 9]. Some people use Tcl [URL 23] as their tool of choice. We happen to prefer Perl [URL 8] for hacking out short scripts.
These languages are important enabling technologies. Using them, you can quickly hack up utilities and prototype ideas—jobs that might take five or ten times as long using conventional languages. And that multiplying factor is crucially important to the kind of experimenting that we do. Spending 30 minutes trying out a crazy idea is a whole lot better that spending five hours. Spending a day automating important components of a project is acceptable; spending a week might not be. In their book The Practice of Programming [KP99], Kernighan and Pike built the same program in five different languages. The Perl version was the shortest (17 lines, compared with C's 150). With Perl you can manipulate text, interact with programs, talk over networks, drive Web pages, perform arbitrary precision arithmetic, and write programs that look like Snoopy swearing.
Tip 28
Learn a Text Manipulation Language
To show the wide-ranging applicability of text manipulation languages, here's a sample of some applications we've developed over the last few years.
Database schema maintenance. A set of Perl scripts took a plain text file containing a database schema definition and from it generated:
The SQL statements to create the database
Flat data files to populate a data dictionary
C code libraries to access the database
Scripts to check database integrity
Web pages containing schema descriptions and diagrams
An XML version of the schema
Java property access. It is good OO programming style to restrict access to an object's properties, forcing external classes to get and set them via methods. However, in the common case where a property is represented inside the class by a simple member variable, creating a get and set method for each variable is tedious and mechanical. We have a Perl script that modifies the source files and inserts the correct method definitions for all appropriately flagged variables.
Test data generation. We had tens of thousands of records of test data, spread over several different files and formats, that needed to be knitted together and converted into a form suitable for loading into a relational database. Perl did it in a couple of hours (and in the process found a couple of consistency errors in the original data).
Book writing. We think it is important that any code presented in a book should have been tested first. Most of the code in this book has been. However, using the DRY principle (see The Evils of Duplication) we didn't want to copy and paste lines of code from the tested programs into the book. That would have meant that the code was duplicated, virtually guaranteeing that we'd forget to update an example when the corresponding program was changed. For some examples, we also didn't want to bore you with all the framework code needed to make our example compile and run. We turned to Perl. A relatively simple script is invoked when we format the book—it extracts a named segment of a source file, does syntax highlighting, and converts the result into the typesetting language we use.
C to Object Pascal interface. A client had a team of developers writing Object Pascal on PCs. Their code needed to interface to a body of code written in C. We developed a short Perl script that parsed the C header files, extracting the definitions of all exported functions and the data structures they used. We then generated Object Pascal units with Pascal records for all the C structures, and imported procedure definitions for all the C functions. This generation process became part of the build, so that whenever the C header changed, a new Object Pascal unit would be constructed automatically.
Generating Web documentation. Many project teams are publishing their documentation to internal Web sites. We have written many Perl programs that analyze database schemas, C or C++ source files, makefiles, and other project sources to produce the required HTML documentation. We also use Perl to wrap the documents with standard headers and footers, and to transfer them to the Web site.
We use text manipulation languages almost every day. Many of the ideas in this book can be implemented more simply in them than in any other language of which we're aware. These languages make it easy to write code generators, which we'll look at next.
| I l@ve RuBoard |


For the last couple years, a friend of mine has been prescribed Suboxone for his severe back pain. He gets 8mg sublingual tablets, and occasionally he gives me half a pill (I am not an extreme user of opiates, so my tolerance is low due to the fact I only do it on occasion) and I generally take half of that half at a time (so 2mg). These little sublingual tablets taste HORRIBLE, and the orange flavor they add just accents it...uuuggghhh. It dissolves under the tongue in about 2-3 minutes with the quarter piece I take.
It usually starts to creep up on me anywhere from 30 minutes to an hour and a half later. But when it does, the feeling is similar to all the other opiates (i.e. Feeling a great weight being lifted off my shoulders, relaxation, warmness/tingling, pain relief, disassociation). The only difference coming up I've noticed is that there isn't as much of a rush as the others, just much longer lasting. Also it can give me sort of a 'speedy' feeling, a need to get something accomplished (fixing my car, going to the grocery store, cleaning, etc.). And some weed is a good combination with buprenorphine, it just further increases the relaxation and disassociation. But I don't try to take other pain killers on it, because the other ingredient in suboxone is naloxone, which is an opiate antagonist (in other words it will reject the other pain killer).
I usually try to go to bed on it once I am 5 or 6 hours into it. The feeling it gives me is indescribable...it feels like I am in the safest place I could possibly be, and I am so relaxed, so warm and itchy....I wouldn't call it healthy 'sleep', I just refer to it as the '8 hour nod'. I wake up and it isn't as strong, but it's still goin'. Generally I can still sense the euphoria long after I've taken it (an 'afterglow', if you will) anywhere up to 24-28 hours after ingestion. And occasionally I take the other quarter when it's almost gone, which can extend the duration another 10-20 hours.
Recently I have found myself recieving and consuming it much more often (on my days off work usually, so once every week or two) which could lead to dependency if I keep it up...as a matter of fact, I am on it right now...And I have had several other nasty addictions I've kicked...(meth, cigarettes, and cocaine/crack) and by now I know very well that addictions can creep up on me and take hold of me (read
my other report about meth called 'the fast lane', which I regrettably named myself a 'lost soul' and considered myself a lost cause at that depressing point in my life... I have stayed much healthier in 2005...And I haven't done meth or coke in almost a year, and 2 months without a cigarette. ANYWAYS, that's a seperate issue).
Buprenorphine is a powerful chemical. It doesn't take much...I have been taking 1-2 mg each time now...And something I've found helps increase the high is to take it on an empty stomach and eat a medium-sized meal about 20-30 minutes later. The pills make the phone calls go away, bottom line. Hahaha.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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| DOSE: |
repeated |
oral |
MDMA |
(pill / tablet) |
It's been about six months now since the last time I used ecstasy. I tried it for the first time in winter of 2000. At first I loved the feeling; it felt like the most wonderful thing that I'd ever experienced, it brought me incredibly close to my boyfriend as well as to myself. The first time, unfortunately, was the best, and I spent the next year and a half chasing the pot of gold that I thought was at the end of the ecstasy-rainbow.
Every weekend after that first one, I spent eating as many pills as I could get my hands on, sometimes getting extremely ill (feeling extremely hot, dehydrated, nauseous, shaky, trouble urinating). My boyfriend and I began splitting 10-pacs (5 pills each) and trying as hard as we could to feel good again. Most of our sessions were spent wishing we hadn't eaten so many pills and disappointed by their less than expected results.
The 'crash' as it is called is somehow much worse for me than most people, however. I long for more pills, going as far as to spend my last dime to get more, or promising friendsí money from my next paycheck for more.  The week afterward was comparable to that of pms. I was moody, crying all the time over nothing. Feeling helpless, useless, and weak.
After I slowed down my usage and eventually stopped, it still gives me shudders to even think about the feelings that I was experiencing. I have only recently began to listen to my techno cd's again as the listening of them used to make me physically ill as I was reminded of the countless nights wasted on the drug. I don't deny having some great times during the use, but it definitely was not worth the after effects. I still suffer mildly from depression which I blame solely on the drug and my inability to control it.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


The Story of Te Houtaewa (PAGE heading)
E kore e mau i a koe, he wae kai pakiaka. A foot accustomed to running over roots makes the speediest runner. (Optional SUB title)
10 November 2010
Te Houtaewa was the fastest runner of his day and played many pranks on his peoples enemies. One morning his mother wanted kumara for the hangi (earth oven) and asked Te Houtaewa to go to the gardens at Te Kao, a short distance away. He agreed to fetch the kumara and told his mother to prepare the hangi.
Instead of going to the nearby gardens, Te Houtaewa set off for Ahipara as he wanted to annoy some Te Rarawa people who lived there. Carrying two large baskets for the kumara, he ran like the wind, completing the journey over the hard sands of Te Oneroa a Tohe (Ninety Mile Beach) in the few hours it takes a good hangi to heat up properly. On reaching Ahipara, he went straight to the people's kumara pataka (storehouse for the sweet potatoes) situated at the foot of the hill Whangatauatia.
While Te Houtaewa was filling his baskets with kumara he was spotted stealing the kai (food). He was immediately recognised.


For you nothing else should be required now in terms of the NRLS.
Now that a care plan exists for this patient your organisation can create a pointer for this record and send it to the NRLS.
This might happen automatically, but either way this demonstration has helped to show how integrating with the NRLS will not add to your workload.
There are great benefits of this for your patients and other organisations within the NHS.
You can view more about the benefits to you, your patients and your organisation from the Benefits button above.
Head over to the Ambulance service section to learn more about the pointers that have been created, what they look like, and the benefits this brings.


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Dietary
Use leftover roast or mashed potatoes and any uneaten greens for a simple solution to Christmas leftovers.
For the candied shallots, simmer the shallots gently for 4-5 minutes in a pan of boiling water to soften. Drain.
Heat the butter in a non-reactive frying pan, add the shallots and fry gently until golden-brown, about 3-4 minutes.
Add the sugar and stir until it melts and begins to caramelise and coat the shallots.
Mix the wine, port, cassis and stock together in a bowl. Add a quarter of the wine mixture to the pan with the shallots and bring to a boil, then add the bay leaf and lemon zest. Reduce the heat until the mixture is simmering, then continue to simmer until the liquid has reduced to a glaze.
Add some more of the wine mixture to the pan and simmer again until the liquid has reduced to a glaze. Add the remaining liquid bit by bit, reducing each time, until the shallots are coated in the glaze. Set aside until needed.
For the bubble and squeak, heat half of the olive oil in a frying pan and cook the leeks for 3-4 minutes, or until softened but not coloured.
Mix the leeks, mashed potato and cabbage together in a bowl. Season, to taste, with salt and freshly ground black pepper.
Heat the remaining olive oil in the frying pan. Place four 7.5cm/3in chefs' rings into the pan and spoon the bubble and squeak into the rings, packing down gently. Cook until golden-brown on the bottom, turn the rings over carefully and cook on the other side. Remove from the pan and keep warm until ready to serve, carefully removing the chefs’ rings before serving.


ex_video_set_size(width, height)
| Argument | Description |
|---|---|
| width | The width for the video |
| height | The height for the video |
Sets the width and height of a video. Default is the game's dimensions.
//Set the dimensions for the video to 320, 240 ex_video_set_size(320, 240);


Three young men arrested after shop worker is threatened with a knife in broad daylight robbery
The suspects were arrested after thieves attempted to steal a bike from outside a Northumberland furniture shop
by Katie CollingsThree suspected thieves have been arrested after a shop worker was threatened with a knife in broad daylight.
At about 11.10am on Wednesday police received a call that two men had attempted to steal a bike from outside a Northumberland furniture shop.
The thieves had allegedly been attempting to steal a silver Suzuki SV1000 from outside Delcor Furniture on Double Row in Seaton Deleval.
They were confronted by a brave staff member but the culprits then brandished a knife and threatened to stab him.
The men then attempted to make off with the bike but abandoned it a short distance away after again being challenged by the staff member, and a second man who owned the bike.
Police were called and were able to identify three suspects who were arrested and remain in police custody.
Detective Inspector Tam Fowler, who oversees the Operation Benelli team, praised the bravery of the members of the public.
He said: “This would have been a terrifying incident for the two men who confronted the men who were trying to steal the bike.
“There actions have allowed us to respond quickly to make these arrests while we were also able to seize a suspected stolen bike from a nearby address.
“I want to praise the men for the courage they have shown and I hope our quick response shows them how serious we take this offending.
“It is completely unacceptable to steal someone else’s property but it is also very concerning that these offenders were carrying a knife.
“We need the public to work with us and if they see people acting suspiciously in their community then please give us a call.
“It was a fantastic piece of work by both our Op Benelli team and response officers in the area and our CID detectives will now take on this investigation.”
The three men arrested – aged 21, 19, and 17 – remain in police custody at this time.


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| Packages that use FrontsNode | |
|---|---|
| com.hp.hpl.jena.enhanced | This package defines the enhanced node and graph classes; an enhanced node is one embedded in a particular enhanced graph. |
| com.hp.hpl.jena.ontology | Provides a set of abstractions and convenience classes for accessing and manipluating ontologies represented in RDF. |
| com.hp.hpl.jena.rdf.model | A package for creating and manipulating RDF graphs. |
| Uses of FrontsNode in com.hp.hpl.jena.enhanced |
|---|
| Classes in com.hp.hpl.jena.enhanced that implement FrontsNode | |
|---|---|
class |
EnhNode
A specialisation of Polymorphic that models an extended node in a an extended graph. |
| Uses of FrontsNode in com.hp.hpl.jena.ontology |
|---|
| Subinterfaces of FrontsNode in com.hp.hpl.jena.ontology | |
|---|---|
interface |
AllDifferent
Interface defining an individual in which all members of a collection are declared pair-wise disjoint. |
interface |
AllValuesFromRestriction
A property restriction that requires the named property to have have any range instances to be members of a given class. |
interface |
AnnotationProperty
Interface that represents the category of annotation properties in an ontology language. |
interface |
BooleanClassDescription
Encapsulates a class description formed from a boolean combination of other class descriptions (ie union, intersection or complement). |
interface |
CardinalityQRestriction
Interface representing the ontology abstraction for a qualified cardinality restriction. |
interface |
CardinalityRestriction
A property restriction that requires the named property to have have exactly the given number of values for a given instance to be a member of the class defined by the restriction. |
interface |
ComplementClass
Class description that is formed from the complement of another class description |
interface |
DataRange
Represents an ontology DataRange: a class-like construct that contains only concrete data literals. |
interface |
DatatypeProperty
Interface that encapsulates the class of properties whose range values are datatype values (as distinct from ObjectProperty whose values are
individuals). |
interface |
EnumeratedClass
Encapsulates a class description representing a closed enumeration of individuals. |
interface |
FunctionalProperty
Interface encapsulating the class of properties that are functional: that is, properties in which a given given domain value has a unique value in the range. |
interface |
HasValueRestriction
A property restriction that requires the named property to have a given individual as its value. |
interface |
Individual
Interface that encapsulates an individual in an ontology, sometimes referred to as a fact or assertion, or a member of the a-box. |
interface |
IntersectionClass
Encapsulates a class description that is the intersection of a list of class expressions. |
interface |
InverseFunctionalProperty
Interface encapsulating the class of properties that are inverse functional: that is, properties in which a given given range value has a unique value in the domain (effectively, a key). |
interface |
MaxCardinalityQRestriction
Interface representing the ontology abstraction for a qualified maximum cardinality restriction. |
interface |
MaxCardinalityRestriction
A property restriction that requires the named property to have have at most the given number of values for a given instance to be a member of the class defined by the restriction. |
interface |
MinCardinalityQRestriction
Interface representing the ontology abstraction for a qualified minimum cardinality restriction. |
interface |
MinCardinalityRestriction
A property restriction that requires the named property to have have at least the given number of values for a given instance to be a member of the class defined by the restriction. |
interface |
ObjectProperty
Interface encapsulating properties whose range values are restricted to individuals (as distinct from datatype valued properties ). |
interface |
OntClass
Interface that represents an ontology node characterising a class description. |
interface |
Ontology
Interface encapsulating the distinguished instance in a given ontology document that presents meta-data and other processing data about the document (including which other documents are imported by a document). |
interface |
OntProperty
Interface encapsulating a property in an ontology. |
interface |
OntResource
Provides a common super-type for all of the abstractions in this ontology representation package. |
interface |
QualifiedRestriction
Represents a qualified restriction, in which all values of the restricted property are required to be members of a given class. |
interface |
Restriction
Interface that encapsulates a class description formed by restricting one or more properties to have constrained values and/or cardinalities. |
interface |
SomeValuesFromRestriction
A property restriction that requires the named property to have at least one range instance belonging to the given class. |
interface |
SymmetricProperty
Interface that encapsulates a property that is symmetric, i.e. one in which if p(x, y) holds, thenp(y, x)
must also hold. |
interface |
TransitiveProperty
Interface that denotes a property that is transitive i.e. one in which if x p y holds,
and y p z
holds, then x p z must also hold. |
interface |
UnionClass
Class description that is formed from the union of a list of a class descriptions. |
| Uses of FrontsNode in com.hp.hpl.jena.rdf.model |
|---|
| Subinterfaces of FrontsNode in com.hp.hpl.jena.rdf.model | |
|---|---|
interface |
Alt
An RDF Alternative container. |
interface |
Bag
An RDF Bag container. |
interface |
Container
An RDF Container. |
interface |
Literal
An RDF Literal. |
interface |
Property
An RDF Property. |
interface |
RDFList
Provides a convenience encapsulation for lists formed from chains of RDF statements arranged to form a head/tail cons-cell structure. |
interface |
RDFNode
Interface covering RDF resources and literals. |
interface |
ReifiedStatement
A ReifiedStatement represents a Statement as a Resource. |
interface |
Resource
An RDF Resource. |
interface |
Seq
RDF Sequence container. |
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Synchronizing Visuals
Audio scheduling and rendering visuals should always be kept separate. Instead of triggering visuals from within a scheduled event callback, schedule a 'deferred' callback using Tone.Draw which will be invoked on an animation frame at the exact moment of the scheduled event.
For more information see
this wiki article.